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Age-space-time CAR models in Bayesian disease mapping.

T Goicoa1,2,3, M D Ugarte1,2, J Etxeberria1,2,4

  • 1Department of Statistics and O. R. Universidad Pública de Navarra, Campus de Arrosadia, Pamplona, 31006, Spain.

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Summary

Prostate cancer mortality declined since the late 1990s, especially in men aged 65-70, likely due to PSA testing and improved early-stage treatments. Older age groups showed less significant declines in cancer mortality rates.

Keywords:
INLAinteraction modelsmortality rates

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Public Health

Background:

  • Cancer mortality data is often aggregated, potentially masking age structure impacts.
  • Spatio-temporal cancer mortality trends may be influenced by evolving demographics.
  • Accurate analysis requires models accounting for age, time, and region interactions.

Purpose of the Study:

  • To analyze prostate cancer mortality rates by region, time, and age group in Spain.
  • To develop and apply statistical models incorporating space-time, space-age, and age-time interactions.
  • To investigate the impact of changing age structures on cancer mortality trends.

Main Methods:

  • Utilized Integrated Nested Laplace Approximation (INLA) for efficient model fitting and inference.
  • Compared INLA with traditional Markov chain Monte Carlo (McMC) methods for reduced computation time.
  • Employed statistical models to analyze spatio-temporal and age-specific cancer mortality patterns.

Main Results:

  • Observed a significant decline in prostate cancer mortality rates starting in the late 1990s.
  • The decline was most pronounced in the 65-70 age group, correlating with PSA testing and early treatment advancements.
  • Mortality decline was less evident in the oldest age cohorts.

Conclusions:

  • Age structure is a critical factor in understanding spatio-temporal cancer mortality dynamics.
  • The study highlights the effectiveness of early detection (PSA test) and treatment in reducing prostate cancer mortality.
  • Further research is needed to understand mortality trends in elderly populations.